code: def run_tf_dataset_with_random_input_gpu(max_shape, dtype, batch):
      min_shape = get_min_shape_helper(batch, max_shape)
      iterator = RandomSampleIterator(
          max_shape, dtype(0), min_shape=min_shape
      )
      run_tf_dataset_graph(
          "gpu",
          get_pipeline_desc=external_source_tester(
              max_shape, dtype, iterator, "gpu", batch=batch
          ),
          to_dataset=external_source_converter_with_callback(
              RandomSampleIterator,
              max_shape,
              dtype,
              0,
              1e10,
              min_shape,
              batch=batch,
          ),
      )
  
imports: import itertools
  import numpy
  import random
  import tensorflow
  from nose.tools import with_setup
  from nose_utils import raises
  from test_dali_tf_dataset_pipelines import FixedSampleIterator, external_source_tester, external_source_converter_with_fixed_value, external_source_converter_with_callback, RandomSampleIterator, external_source_converter_multiple, get_min_shape_helper, external_source_tester_multiple
  from test_dali_tf_es_pipelines import external_source_to_tf_dataset, gen_tf_with_dali_external_source, get_external_source_pipe
  from test_utils_tensorflow import run_tf_dataset_graph, skip_inputs_for_incompatible_tf, run_dataset_in_graph, run_tf_dataset_multigpu_graph_manual_placement, get_dali_dataset_from_pipeline, get_image_pipeline
label_desc: Use image node_id 7 for calling a global function with example usage: run_tf_dataset_with_random_input_gpu(max_shape, dtype, batch) without return types